Anzeige
Erschienen in:
2007 | OriginalPaper | Buchkapitel
Evolutionary Testing: A Case Study
verfasst von : Stella Levin, Amiram Yehudai
Erschienen in: Hardware and Software, Verification and Testing
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
The paper presents a case study of applying genetic algorithms (GAs) to the automatic test data generation problem. We present the basic techniques implemented in our prototype test generation system, whose goal is to get branch coverage of the program under testing. We used our tool to experiment with simple programs, programs that have been used by others for test strategies benchmarking and the UNIX utility uniq. The effectiveness of GA-based testing system is compared with a Random testing system. We found that for simple programs both testing systems work fine, but as the complexity of the program or the complexity of input domain grows, GA-based testing system significantly outperforms Random testing.